Helped develop and assess models and key performance indicators (KPIs) for energy usage. Designed methods to measure change after some event (causal inference) using counter-factuals, and corresponding uncertainty. Provided strategic direction and best practices related to code, machine learning systems, and parallelizing analysis. Technologies included python + python analysis tools, starcluster, AWS cloud

• ASHRAE 14 definition of savings
• New definition of savings based on counterfactual & building models
• ML pipeline parallelization